Authors
Said Jawad Saidi, Anna Maria Mandalari, Hamed Haddadi, Daniel J Dubois, David Choffnes, Georgios Smaragdakis, Anja Feldmann
Publication date
2021/7/24
Book
Proceedings of the Applied Networking Research Workshop
Pages
36-38
Description
Internet of Things (IoT) devices are becoming increasingly popular and offer a wide range of services and functionality to their users. However, there are significant privacy and security risks associated with these devices. IoT devices can infringe users' privacy by ex-filtrating their private information to third parties, often without their knowledge.
In this work we investigate the possibility to identify IoT devices and their location in an Internet Service Provider's network. By analyzing data from a large Internet Service Provider (ISP), we show that it is possible to recognize specific IoT devices, their vendors, and sometimes even their specific model, and to infer their location in the network. This is possible even with sparsely sampled flow data that are often the only datasets readily available at an ISP. We evaluate our proposed methodology [1] to infer IoT devices at subscriber lines of a large ISP. Given ground truth …
Total citations
202220232024233
Scholar articles
SJ Saidi, AM Mandalari, H Haddadi, DJ Dubois… - Proceedings of the Applied Networking Research …, 2021